An Optimization Algorithm H-GVSPM for Electrical Impedance Tomography

Electrical impedance tomography (EIT) is a novel industrial monitoring technology with the characteristics of safety, inexpensiveness, and real-time monitoring. Its imaging results are easily to generate artifacts due to the influence of various factors. Therefore, the image quality is low, and the contour of measured objects has a distortion phenomenon. An optimization algorithm H-GVSPM based on the Hadamard product is proposed for EIT to reduce the artifacts, and to improve the image quality. The relative conductivity difference between the measured object and the background becomes more distinguishable with the action of the Hadamard product. Simulation and experimental results show that H-GVSPM effectively reduces the influence of artifacts in the reconstructed images. The maximum increase of the correlation coefficient approximately is 15.56% and 22.80% respectively compared with GVSPM and TV method. The maximum reduction of the voltage relative residual is 22.12% in the simulation, and it is 8.12% in the experiment. The standard deviation of conductivity is about 1/10 of the original. This study provides a reference method for improving image quality, and it contributes to the application of EIT in industry, biomedicine, and other fields in the future.

Automated summary

Electrical impedance tomography (EIT) is a novel industrial monitoring technology that offers safety, inexpensiveness, and real-time monitoring. A new optimization algorithm called H-GVSPM based on the Hadamard product is proposed in this study to reduce artifacts and improve image quality in EIT. Simulation and experimental results show that H-GVSPM effectively reduces artifacts in reconstructed images and increases the correlation coefficient compared to GVSPM and TV methods. This study provides a reference method for improving image quality and contributes to the future application of EIT in industry, biomedicine, and other fields.